Open AccessTorque measurements from MW wind turbine Gearboxes: a system identification approach
Author(s) -
Unai Gutierrez Santiago,
JanWillem van Wingerden,
H. Polinder,
Alfredo Fernández Sisón
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1618/2/022027
Subject(s) - torque , turbine , wind power , test bench , harmonics , engineering , system identification , stiffness , drivetrain , control theory (sociology) , computer science , control engineering , automotive engineering , mechanical engineering , data modeling , structural engineering , physics , electrical engineering , software engineering , control (management) , voltage , artificial intelligence , thermodynamics
The gearbox is a critical component of modern MW wind turbines. An accurate model of the gearbox dynamics is needed to improve gearbox design, develop advanced control algorithms, and more effective fault diagnosis tools which could lead to lower the cost of energy from wind. The objective of this paper is to investigate how torque measurements can be used in a data-driven framework to build dynamic models of wind turbine gearboxes. An initial torsional model has been derived from first principles considering the stiffness of the gears, shafts, and structural components in the gearbox together with the mechanical components of the test bench. This model has been used to create simulated data of the experiments performed on gearboxes and to apply system identification techniques to the simulated signals, with a focus on predictor based subspace identification methods. System identification has been applied to torque and speed data measured on physical tests of two 3.4MW gearboxes. Gearbox excitation frequencies and their harmonics dominate the measured signals and disturb the system identification algorithms. Several techniques have been investigated to remove the shaft rotation and gear mesh frequency harmonics of the torque and rotational speed signals based on time synchronous averaging.